| Literature DB >> 31835300 |
Qingyuan Zhao1,2, Jianting Zhou1,2, Qianwen Xia1,2, Senhua Zhang1,2, Hong Zhang1,2.
Abstract
In an actual structure, the arrangement of steel bars is complicated, there are many factors affecting the corrosion of steel bars, and these factors affect each other. However, accurately reflecting the corrosion of steel bars in actual engineering through theoretical calculations is difficult. Besides, it is impossible to detect and evaluate steel bars rust completely and accurately. This article is based on spontaneous magnetic leakage detection technology and adopts the method of stage corrosion and scanning along the reinforcing bar. Based on spontaneous magnetic flux leakage detection technology, the linear change rate of the tangential component curve of the magnetic flux leakage signal generated after the corrosion of a steel bar is studied, and a comparison is made between the steel bar coated concrete samples with different steel bar diameters. In this paper, the "origin of magnetic flux leakage signal" is defined as a reference point, which is convenient for effectively comparing the magnetic signal curves under all operating conditions. Besides, the "rust-magnetic fluctuation parameter" is proposed to accurately reflect the sudden change of leakage magnetic field caused by disconnection due to the corrosion of a steel bar. A new data processing method is provided for the non-destructive testing of steel corrosion using the spontaneous magnetic flux leakage effect, which can effectively reduce the influence of steel bar diameter on magnetic flux leakage signal and improve the precision of non-destructive testing technology of steel bar corrosion using the metal magnetic memory effect.Entities:
Keywords: non-destructive testing; spontaneous magnetic flux leakage; steel bar corrosion; steel bar outer cladding
Year: 2019 PMID: 31835300 PMCID: PMC6947034 DOI: 10.3390/ma12244116
Source DB: PubMed Journal: Materials (Basel) ISSN: 1996-1944 Impact factor: 3.623
Chemical composition of the rebar (mass fraction).
| Type of Steel | Chemical Composition | ||||
|---|---|---|---|---|---|
| C | Si | Mn | P | S | |
|
| 0.2 | 0.4 | 1.3 | 0.03 | 0.02 |
Number and naming of steel-reinforced concrete specimens.
| Number | Name | Number | Name |
|---|---|---|---|
| 1# | 2000-120-30-a | 13# | 2000-120-30-b |
| 2# | 2000-120-40-a | 14# | 2000-120-40-b |
| 3# | 2000-120-50-a | 15# | 2000-120-50-b |
| 4# | 2000-160-30-a | 16# | 2000-160-30-b |
| 5# | 2000-160-40-a | 17# | 2000-160-40-b |
| 6# | 2000-160-50-a | 18# | 2000-160-50-b |
| 7# | 1500-120-30-a | 19# | 1500-120-30-b |
| 8# | 1500-120-40-a | 20# | 1500-120-40-b |
| 9# | 1500-120-50-a | 21# | 1500-120-50-b |
| 10# | 1500-160-30-a | 22# | 1500-160-30-b |
| 11# | 1500-160-40-a | 23# | 1500-160-40-b |
| 12# | 1500-160-50-a | 24# | 1500-160-50-b |
Figure 1Automatic three-axis magnetic signal testing device.
Figure 2Schematic diagram of rusting of steel-reinforced concrete specimens.
Figure 3Photograph of the test piece rust test.
Figure 4Schematic diagram of the scan path.
Figure 5Schematic diagram of the notched magnetic dipole model of the trapezoidal slot.
Figure 6Schematic calculation of the B component of the magnetic flux leakage signal along the y-axis direction under various corrosion conditions.
Figure 7Variation of magnetic signal B during rusting of test piece under various rust conditions as (a) test piece 1; (b) test piece 2; (c) test piece 3; and (d) test piece 4.
Figure 8Schematic diagram of magnetic signal origin selection.
Figure 9Mc-Time curve comparing the diameter of the steel bar.
Calculation of corrosion rate with corrosion width of 100 mm.
| Rebar Diameter | 12 h | 24 h | 36 h | 48 h | 60 h | 72 h | 84 h | 96 h | 108 h | 120 h |
|---|---|---|---|---|---|---|---|---|---|---|
|
| 14.2% | 28.4% | 42.5% | 56.7% | 70.9% | 85.1% | 99.3% | 113.4% | 127.6% | 141.8% |
|
| 8.0% | 16.0% | 23.9% | 31.9% | 39.9% | 47.9% | 55.8% | 63.8% | 71.8% | 79.8% |
Calculation of corrosion rate with corrosion width of 150 mm.
| Rebar Diameter | 12 h | 24 h | 36 h | 48 h | 60 h | 72 h | 84 h | 96 h | 108 h | 120 h |
|---|---|---|---|---|---|---|---|---|---|---|
|
| 9.5% | 18.9% | 28.4% | 37.8% | 47.3% | 56.7% | 66.2% | 75.6% | 85.1% | 94.5% |
|
| 5.3% | 10.6% | 16.0% | 21.3% | 26.6% | 31.9% | 37.2% | 42.5% | 47.9% | 53.2% |